Papers
Outlier-Robust Optimal Transport: Duality, Structure, and Statistical Analysis
Sloan Nietert, Ziv Goldfeld, Rachel Cummings
PAC Learning of Quantum Measurement Classes : Sample Complexity Bounds and Universal Consistency
Arun Padakandla, Abram Magner
PACm-Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime
Warren R. Morningstar, Alex Alemi, Joshua V. Dillon
PAC Mode Estimation using PPR Martingale Confidence Sequences
Shubham Anand Jain, Rohan Shah, Sanit Gupta et al.
PAC Top-$k$ Identification under SST in Limited Rounds
Arpit Agarwal, Sanjeev Khanna, Prathamesh Patil
Pairwise Fairness for Ordinal Regression
Matthäus Kleindessner, Samira Samadi, Muhammad Bilal Zafar et al.
Pairwise Supervision Can Provably Elicit a Decision Boundary
Han Bao, Takuya Shimada, Liyuan Xu et al.
Parallel MCMC Without Embarrassing Failures
Daniel A. De Souza, Diego Mesquita, Samuel Kaski et al.
Parameter-Free Online Linear Optimization with Side Information via Universal Coin Betting
Jongha J. Ryu, Alankrita Bhatt, Young-Han Kim
Parametric Bootstrap for Differentially Private Confidence Intervals
Cecilia Ferrando, Shufan Wang, Daniel Sheldon
Pareto Optimal Model Selection in Linear Bandits
Yinglun Zhu, Robert Nowak
Particle-based Adversarial Local Distribution Regularization
Thanh Nguyen-Duc, Trung Le, He Zhao et al.
Performative Prediction in a Stateful World
Gavin Brown, Shlomi Hod, Iden Kalemaj
Permutation Equivariant Layers for Higher Order Interactions
Horace Pan, Risi Kondor
p-Generalized Probit Regression and Scalable Maximum Likelihood Estimation via Sketching and Coresets
Alexander Munteanu, Simon Omlor, Christian Peters
Physics Informed Deep Kernel Learning
Zheng Wang, Wei Xing, Robert Kirby et al.
Pick-and-Mix Information Operators for Probabilistic ODE Solvers
Nathanael Bosch, Filip Tronarp, Philipp Hennig
Point Cloud Generation with Continuous Conditioning
Larissa T. Triess, Andre Bühler, David Peter et al.
Policy Learning and Evaluation with Randomized Quasi-Monte Carlo
Sébastien M. R. Arnold, Pierre L’Ecuyer, Liyu Chen et al.
Policy Learning for Optimal Individualized Dose Intervals
Guanhua Chen, Xiaomao Li, Menggang Yu
Polynomial Time Reinforcement Learning in Factored State MDPs with Linear Value Functions
Zihao Deng, Siddartha Devic, Brendan Juba
Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums
Kaiwen Zhou, Lai Tian, Anthony Man-Cho So et al.
Predicting the impact of treatments over time with uncertainty aware neural differential equations.
Edward De Brouwer, Javier Gonzalez, Stephanie Hyland
Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach
Setareh Ariafar, Justin Gilmer, Zachary Nado et al.
Predictive variational Bayesian inference as risk-seeking optimization
Futoshi Futami, Tomoharu Iwata, Naonori Ueda et al.